Senior Lecturer in Computer Science
I hold an MSc/MPhil in Applied Mathematics and Mechanics from the Novosibirsk University, Academgorodok, Russia.
My PhD is in Application of Computer Technology, Mathematical Modelling and Mathematical Methods in Scientific Research, from the Institute of Information Technologies and Applied Mathematics, Russian Academy of Sciences.
I came to Sunderland in 2000 from Sydney, Australia where I worked for the Statistical Hydrology Unit, River Management Branch, Department of Water Resources, NSW Government; Macquarie University and University of Technology as a researcher/lecturer. In Sydney, I also ran my own consultancy business (P-Quant) in computer science, mathematics and statistics.
Teaching and supervision
- Research Skills and Academic Literacy
- Intelligent Systems for Management
- Decision Support for Management
- Managing People and Organisational Development
- Managing People and Project Leadership
I supervise PhD students in the interdisciplinary areas of Machine Learning, Data Mining, Data Science and Big Data.
Some recent research projects are relevant to Learning of Noise Web Data, Ant Colony Optimisation, Application of Profile Theory and Association Rule Mining.
I supervise MSc Projects for MSc Information Technology Management, MSc Project Management and MSc Engineering Management.
Research interests for potential research students
I am the author of new mathematical theory - Profile Theory, which has a number of practical applications, in the fields of Business Intelligence; Data Science, Machine Learning, Data Mining, Software/Web Engineering; Computational Intelligence.
If you you are highly motived and have a strong interest in these research areas please feel free to contact me directly to discuss relevant research opportunities.
In 1997, I invented a new mathematical theory - Profile Theory, which has a number of practical applications, e.g. in the fields of Business Intelligence, Data Science, Machine Learning, Data Mining, Software/Web Engineering, Computational Intelligence.
In large measure, Profile Theory is designed to address an important class of problems, which are not addressed by the traditional theories (it includes complex systems theories) in which the central issues relate to capability and compatibility problems of complex systems and/or their elements; and determination of complex system structures. The importance of Profile Theory derives from the fact that in the real world such problems are the norm rather than exception.
Key research issues include: analysis and modelling of complex systems where capabilities and compatibilities of their elements are critical factors.
Onyancha, Julius and Plekhanova, Valentina (2018) ‘Noise Reduction in Web Data: A Learning Approach Based on Dynamic User Interests'. International Journal of Information and Education Technology, 12 (1). pp. 7-14. ISSN 2010-3689
Plekhanova, Valentina, Smith, Peter and Hamdan, Khaled (2012) A Role of Quality of Information for Innovation: Leadership Style and Information Management. Proceedings of the Eighth International Conference on Innovations in Information Technology (Innovations '12). 344 -349. ISSN 1569543409
Hamdan, Khaled, Smith, Peter and Plekhanova, Valentina (2012) Leadership and Cultural Issues: Evaluation and Measurement in the Context of Software Development Projects. International Journal of Information and Education Technology, 2 (1). pp. 68-76. ISSN 2010-3689
Plekhanova, Valentina (2003) Co-operative Learning in Cognitive Systems. Mathematical Modelling, 12 (15). pp. 109-118.
Onyancha, Julius, Plekhanova, Valentina and Nelson, David (2018) Learning Noise in Web Data Prior to Elimination. In: Transactions on Engineering Technologies: 25th World Congress on Engineering (WCE 2017). Springer. ISBN 9789811307461
Plekhanova, Valentina (2018) A Capability and Compatibility Approach to Modelling of Information Reuse and Integration for Innovation. In: Advances in Internet, Data & Web Technologies: The 6th International Conference on Emerging Internet, Data & Web Technologies. Lecture Notes on Data Engineering and Communications Technologies (ISSN: 2367-4512) . Springer. ISBN 9783319759272
Onyancha, Julius, Plekhanova, Valentina and Nelson, David (2017) Noise Web Data Learning from a Web User Profile: Position Paper. In: , Lecture Notes in Engineering and Computer Science: Proceedings of The World Congress on Engineering 2017 Volume II. IAENG, pp. 608-611. ISBN 978-988-14048-3-1
Plekhanova, Valentina (2009) Learning Systems Engineering. In: Encyclopedia of Information Science and Technology. Information Science Reference, pp. 2404-2410. ISBN 978-1- 60566-026-4
Plekhanova, Valentina (2005) Learning Systems Engineering. In: Encyclopedia of Information Science and Technology. Idea Group Inc., pp. 1820-1826. ISBN 159140553X
Plekhanova, Valentina (2005) Respecting Diverse Talents and Ways of Learning. In: Encylopedia of Distance Learning (C. Howard, J.V. Boetttcher, L. Justice, K. Schenk P.L. Rogers and G.A. Berg Eds.). Idea Group Inc., pp. 1573-1580. ISBN 1591405556
Bokma, Albert, Tsakopoulos, Stamatios and Plekhanova, Valentina (2003) Partner Evaluation and Selection in Virtual Enterprises Using a Profile Theory Based Approach. In: Processes and Foundations for Virtual Organisations. Kluwer Academic Publishers, pp. 73-84. ISBN 140207638X
Conference or Workshop Item
Onyancha, Julius and Plekhanova, Valentina (2018) A user-centric approach towards learning noise in web data. In: 12th International Conference on Intelligent Systems and Knowledge Control, 24-26 Nov 2017, Nanjing, Jiangsu.
Onyancha, Julius, Plekhanova, Valentina and Nelson, David (2017) Noise Web Data Learning from a Web User Profile: Position Paper. In: WCE 2017, 5-7 Jul 2017, London, UK.
Hamdan, Khaled, Smith, Peter and Plekhanova, Valentina (2011) A Formal Approach to the Measurement of Leadership and Cultural Capabilities. In: International Conference on Engineering and Information Management (ICEIM 2011), 15-17 Apr 2011, Chengdu, China.
Plekhanova, Valentina (2004) Concurrent Engineering the Virtual Enterprises: Agents and their Structural Organisation. In: Proceedings of the 11th European Concurrent Engineering Conference (ECEC 2004): Worldwide Partnerships and Mergers.
- Data Mining
- Machine Learning
- Data Science
- Data Analytics
- Big Data
- Knowledge Engineering
- Computational Intelligence and Intelligent Systems
- Business Intelligence
I am a member of a number of International Conference Programme Committees including:
- International Conference of Data Mining and Knowledge Engineering
- International Conference of Computational Intelligence and Intelligent Systems
- International Conference on Fuzzy Computation
- International Conference on Business Intelligence and Data Warehouse
- International Conference on Software Engineering; International Conference on Green IT
- International Conference on Fuzzy Computation Theory and Applications
- International Conference on Natural Computation
- International Conference on Fuzzy Systems and Knowledge Discovery